Browsing by Author "Liang, Chao"

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A new method for post Genome-Wide Association Study (GWAS) analysis of colorectal cancer in Taiwan
(2013-04-10)
Wang, Hwei-Ming
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Chang, Tzu-Hao
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Lin, Feng-Mao
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Chao, Te-Hsin
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Huang, Wei-Chih
Recently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development. (c) 2012 Elsevier B.V. All rights reserved.
Bacterial alterations in salivary microbiota and their association in oral cancer
(2017-11-28)
Lee, Wei-Hsiang
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Chen, Hui-Mei
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Yang, Shun-Fa
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Liang, Chao
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Peng, Chih-Yu
Oral squamous cell carcinoma (OSCC) is the most common malignant neoplasm of the oral cavity and the fourth leading malignancy and cause of cancer-related death in the male population of Taiwan. Most cases are detected at advanced stages, resulting in poor prognosis. Therefore, improved detection of early oral health disorders is indispensable. The involvement of oral bacteria in inflammation and their association with OSCC progression provide a feasible target for diagnosis. Due to the nature of oral neoplasms, the diagnosis of epithelial precursor lesions is relatively easy compared with that of other types of cancer. However, the transition from an epithelial precursor lesion to cancer is slow and requires further and continuous follow-up. In this study, we investigated microbiota differences between normal individuals, epithelial precursor lesion patients, and cancer patients with different lifestyle habits, such as betel chewing and smoking, using next-generation sequencing. Overall, the oral microbiome compositions of five genera, Bacillus, Enterococcus, Parvimonas, Peptostreptococcus, and Slackia, revealed significant differences between epithelial precursor lesion and cancer patients and correlated with their classification into two clusters. These composition changes might have the potential to constitute a biomarker to help in monitoring the oral carcinogenesis transition from epithelial precursor lesion to cancer.
Bacterial Communities in Semen from Men of Infertile Couples: Metagenomic Sequencing Reveals Relationships of Seminal Microbiota to Semen Quality
(2014-10-23)
Weng, Shun-Long
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Chiu, Chih-Min
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Lin, Feng-Mao
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Huang, Wei-Chih
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Liang, Chao
Some previous studies have identified bacteria in semen as being a potential factor in male infertility. However, only few types of bacteria were taken into consideration while using PCR-based or culturing methods. Here we present an analysis approach using next-generation sequencing technology and bioinformatics analysis to investigate the associations between bacterial communities and semen quality. Ninety-six semen samples collected were examined for bacterial communities, measuring seven clinical criteria for semen quality (semen volume, sperm concentration, motility, Kruger\'s strict morphology, antisperm antibody (IgA), Atypical, and leukocytes). Computer-assisted semen analysis (CASA) was also performed. Results showed that the most abundant genera among all samples were Lactobacillus (19.9%), Pseudomonas (9.85%), Prevotella (8.51%) and Gardnerella (4.21%). The proportion of Lactobacillus and Gardnerella was significantly higher in the normal samples, while that of Prevotella was significantly higher in the low quality samples. Unsupervised clustering analysis demonstrated that the seminal bacterial communities were clustered into three main groups: Lactobacillus, Pseudomonas, and Prevotella predominant group. Remarkably, most normal samples (80.6%) were clustered in Lactobacillus predominant group. The analysis results showed seminal bacteria community types were highly associated with semen health. Lactobacillus might not only be a potential probiotic for semen quality maintenance, but also might be helpful in countering the negative influence of Prevotella and Pseudomonas. In this study, we investigated whole seminal bacterial communities and provided the most comprehensive analysis of the association between bacterial community and semen quality. The study significantly contributes to the current understanding of the etiology of male fertility.
Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing
(2013)
Chiu, Chih-Min
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Lin, Feng-Mao
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Chang, Tzu-Hao
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Huang, Wei-Chih
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Liang, Chao
The human body plays host to a vast array of bacteria which are harmful or beneficial. Next generation sequencing technology have increased its accuracy in identifying bacteria. This work develops a novel platform for rapidly detecting probiotics and pathogens based on sequencing results of 16S rRNA. A database that recorded the species of probiotics and pathogens from literature was constructed, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. A bacteria disease risk model for seven diseases was constructed based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species for clinical microbiology applications. Detecting how probiotics and pathogens inhabit humans and affect their health significantly contributes to develop a diagnosis and treatment method.
Diversity and enterotype in gut bacterial community of adults in Taiwan
(2017-01-01)
Liang, Chao
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Tseng, Han-Chi
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Chen, Hui-Mei
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Wang, Wei-Chi
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Chiu, Chih-Min
Background: Gastrointestinal microbiota, particularly gut microbiota, is associated with human health. The biodiversity of gut microbiota is affected by ethnicities and environmental factors such as dietary habits or medicine intake, and three enterotypes of the human gut microbiome were announced in 2011. These enterotypes are not significantly correlated with gender, age, or body weight but are influenced by long-term dietary habits. However, to date, only two enterotypes (predominantly consisting of Bacteroides and Prevotella) have shown these characteristics in previous research; the third enterotype remains ambiguous. Understanding the enterotypes can improve the knowledge of the relationship between microbiota and human health. Results: We obtained 181 human fecal samples from adults in Taiwan. Microbiota compositions were analyzed using next-generation sequencing (NGS) technology, which is a culture-independent method of constructing microbial community profiles by sequencing 16S ribosomal DNA (rDNA). In these samples, 17,675,898 sequencing reads were sequenced, and on average, 215 operational taxonomic units (OTUs) were identified for each sample. In this study, the major bacteria in the enterotypes identified from the fecal samples were Bacteroides, Prevotella, and Enterobacteriaceae, and their correlation with dietary habits was confirmed. A microbial interaction network in the gut was observed on the basis of the amount of short-chain fatty acids, pH value of the intestine, and composition of the bacterial community (enterotypes). Finally, a decision tree was derived to provide a predictive model for the three enterotypes. The accuracies of this model in training and independent testing sets were 97.2 and 84.0%, respectively. Conclusions: We used NGS technology to characterize the microbiota and constructed a predictive model. The most significant finding was that Enterobacteriaceae, the predominant subtype, could be a new subtype of enterotypes in the Asian population.
Diversity and enterotype in gut bacterial community of adults in Taiwan
(2017-01-25)
Liang, Chao
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Tseng, Han-Chi
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Chen, Hui-Mei
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Wang, Wei-Chi
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Chiu, Chih-Min
Background: Gastrointestinal microbiota, particularly gut microbiota, is associated with human health. The biodiversity of gut microbiota is affected by ethnicities and environmental factors such as dietary habits or medicine intake, and three enterotypes of the human gut microbiome were announced in 2011. These enterotypes are not significantly correlated with gender, age, or body weight but are influenced by long-term dietary habits. However, to date, only two enterotypes (predominantly consisting of Bacteroides and Prevotella) have shown these characteristics in previous research; the third enterotype remains ambiguous. Understanding the enterotypes can improve the knowledge of the relationship between microbiota and human health. Results: We obtained 181 human fecal samples from adults in Taiwan. Microbiota compositions were analyzed using next-generation sequencing (NGS) technology, which is a culture-independent method of constructing microbial community profiles by sequencing 16S ribosomal DNA (rDNA). In these samples, 17,675,898 sequencing reads were sequenced, and on average, 215 operational taxonomic units (OTUs) were identified for each sample. In this study, the major bacteria in the enterotypes identified from the fecal samples were Bacteroides, Prevotella, and Enterobacteriaceae, and their correlation with dietary habits was confirmed. A microbial interaction network in the gut was observed on the basis of the amount of short-chain fatty acids, pH value of the intestine, and composition of the bacterial community (enterotypes). Finally, a decision tree was derived to provide a predictive model for the three enterotypes. The accuracies of this model in training and independent testing sets were 97.2 and 84.0%, respectively. Conclusions: We used NGS technology to characterize the microbiota and constructed a predictive model. The most significant finding was that Enterobacteriaceae, the predominant subtype, could be a new subtype of enterotypes in the Asian population.
Enterotype-based Analysis of Gut Microbiota along the Conventional Adenoma-Carcinoma Colorectal Cancer Pathway
(2019-07-29)
Yang, Tzu-Wei
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Lee, Wei-Hsiang
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Tu, Siang-Jyun
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Huang, Wei-Chih
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Chen, Hui-Mei
The dysbiosis of human gut microbiota is strongly associated with the development of colorectal cancer (CRC). The dysbiotic features of the transition from advanced polyp to early-stage CRC are largely unknown. We performed a 16S rRNA gene sequencing and enterotype-based gut microbiota analysis study. In addition to Bacteroides-and Prevotella-dominated enterotypes, we identified an Escherichia-dominated enterotype. We found that the dysbiotic features of CRC were dissimilar in overall samples and especially Escherichia-dominated enterotype. Besides a higher abundance of Fusobacterium, Enterococcus, and Aeromonas in all CRC faecal microbiota, we found that the most notable characteristic of CRC faecal microbiota was a decreased abundance of potential beneficial butyrate-producing bacteria. Notably, Oscillospira was depleted in the transition from advanced adenoma to stage 0 CRC, whereas Haemophilus was depleted in the transition from stage 0 to early-stage CRC. We further identified 7 different CAGs by analysing bacterial clusters. The abundance of microbiota in cluster 3 significantly increased in the CRC group, whereas that of cluster 5 decreased. The abundance of both cluster 5 and cluster 7 decreased in the Escherichia-dominated enterotype of the CRC group. We present the first enterotype-based faecal microbiota analysis. The gut microbiota of colorectal neoplasms can be influenced by its enterotype.
Impact of Enterobius vermicularis infection and mebendazole treatment on intestinal microbiota and host immune response
(2017-09-01)
Yang, Chin-An
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Liang, Chao
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Lin, Chia-Li
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Hsiao, Chiung-Tzu
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Peng, Ching-Tien
Background Previous studies on the association of enterobiasis and chronic inflammatory diseases have revealed contradictory results. The interaction of Enterobius vermicularis infection in particular with gut microbiota and induced immune responses has never been thoroughly examined. Methodology/Findings In order to answer the question of whether exposure to pinworm and mebendazole can shift the intestinal microbial composition and immune responses, we recruited 109 (30 pinwormnegative, 79 pinworm-infected) first and fourth grade primary school children in Taichung, Taiwan, for a gut microbiome study and an intestinal cytokine and SIgA analysis. In the pinworm-infected individuals, fecal samples were collected again at 2 weeks after administration of 100 mg mebendazole. Gut microbiota diversity increased after Enterobius infection, and it peaked after administration of mebendazole. At the phylum level, pinworm infection and mebendazole deworming were associated with a decreased relative abundance of Fusobacteria and an increased proportion of Actinobacteria. At the genus level, the relative abundance of the probiotic Bifidobacterium increased after enterobiasis and mebendazole treatment. The intestinal SIgA level was found to be lower in the pinworm-infected group, and was elevated in half of the mebendazole-treated group. A higher proportion of pre-treatment Salmonella spp. was associated with a non-increase in SIgA after mebendazole deworming treatment. Conclusions/Significance Childhood exposure to pinworm plus mebendazole is associated with increased bacterial diversity, an increased abundance of Actinobacteria including the probiotic Bifidobacterium, and a decreased proportion of Fusobacteria. The gut SIgA level was lower in the pinworminfected group, and was increased in half of the individuals after mebendazole deworming treatment.
miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions
(2018-01-04)
Chou, Chih-Hung
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Shrestha, Sirjana
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Yang, Chi-Dung
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Chang, Nai-Wen
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Lin, Yu-Ling
MicroRNAs (miRNAs) are small non-coding RNAs of similar to 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased similar to 1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/.
miRTarBase: a database curates experimentally validated microRNA-target interactions
(2011-01-01)
Hsu, Sheng-Da
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Lin, Feng-Mao
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Wu, Wei-Yun
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Liang, Chao
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Huang, Wei-Chih
MicroRNAs (miRNAs), i.e. small non-coding RNA molecules (similar to 22 nt), can bind to one or more target sites on a gene transcript to negatively regulate protein expression, subsequently controlling many cellular mechanisms. A current and curated collection of miRNA-target interactions (MTIs) with experimental support is essential to thoroughly elucidating miRNA functions under different conditions and in different species. As a database, miRTarBase has accumulated more than 3500 MTIs by manually surveying pertinent literature after data mining of the text systematically to filter research articles related to functional studies of miRNAs. Generally, the collected MTIs are validated experimentally by reporter assays, western blot, or microarray experiments with overexpression or knockdown of miRNAs. miRTarBase curates 3576 experimentally verified MTIs between 657 miRNAs and 2297 target genes among 17 species. miRTarBase contains the largest amount of validated MTIs by comparing with other similar, previously developed databases. The MTIs collected in the miRTarBase can also provide a large amount of positive samples to develop computational methods capable of identifying miRNA-target interactions. miRTarBase is now available on http://miRTarBase.mbc.nctu.edu.tw/, and is updated frequently by continuously surveying research articles.
Systematic Analysis of the Association between Gut Flora and Obesity through High-Throughput Sequencing and Bioinformatics Approaches
(2014)
Chiu, Chih-Min
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Huang, Wei-Chih
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Weng, Shun-Long
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Tseng, Han-Chi
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Liang, Chao
Eighty-one stool samples from Taiwanese were collected for analysis of the association between the gut flora and obesity. The supervised analysis showed that the most, abundant genera of bacteria in normal samples (from people with a body mass index (BMI) <= 24) were Bacteroides (27.7%), Prevotella (19.4%), Escherichia (12%), Phascolarctobacterium(3.9%), and Eubacterium (3.5%). The most abundant genera of bacteria in case samples (with a BMI >= 27) were Bacteroides (29%), Prevotella (21%), Escherichia (7.4%), Megamonas (5.1%), and Phascolarctobacterium (3.8%). A principal coordinate analysis (PCoA) demonstrated that normal samples were clustered more compactly than case samples. An unsupervised analysis demonstrated that bacterial communities in the gut were clustered into two main groups: N-like and OB-like groups. Remarkably, most normal samples (78%) were clustered in the N-like group, and most case samples (81%) were clustered in the OB-like group (Fisher\'s P value = 1.61E-07). The results showed that bacterial communities in the gut were highly associated with obesity. This is the first study in Taiwan to investigate the association between human gut flora and obesity, and the results provide new insights into the correlation of bacteria with the rising trend in obesity.
Vaginal microbiome variances in sample groups categorized by clinical criteria of bacterial vaginosis
(2018-12-31)
Chen, Hui-Mei
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Chang, Tzu-Hao
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Lin, Feng-Mao
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Liang, Chao
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Chiu, Chih-Min
BackgroundOne of the most common and recurrent vaginal infections is bacterial vaginosis (BV). The diagnosis is based on changes to the normal vaginal microbiome; however, the normal microbiome appears to differ according to reproductive status and ethnicity, and even among individuals within these groups. The Amsel criteria and Nugent score test are widely used for diagnosing BV; however, these tests are based on different criteria, and so may indicate distinct changes in the vaginal microbial community. Nevertheless, few studies have compared the results of these test against metagenomics analysis.MethodsVaginal flora samples from 77 participants were classified according to the Amsel criteria and Nugent score test. The microbiota composition was analyzed using 16S ribosome RNA gene amplicon sequencing. Bioinformatics analysis and multivariate statistical analysis were used to evaluate the microbial diversity and function.ResultsOnly 3 % of the participants diagnosed BV negative using the Amsel criteria (A-) were BV-positive according to the Nugent score test (N+), while over half of the BV-positive patients using the Amsel criteria (A+) were BV-negative according to the Nugent score test (N-). Thirteen genera showed significant differences in distribution among BV status defined by BV tests (e.g., A-N-, A+N- and A+N+). Variations in the four most abundant taxa, Lactobacillus, Gardnerella, Prevotella, and Escherichia, were responsible for most of this dissimilarity. Furthermore, vaginal microbial diversity differed significantly among the three groups classified by the Nugent score test (N-, N+, and intermediate flora), but not between the Amsel criteria groups. Numerous predictive microbial functions, such as bacterial chemotaxis and bacterial invasion of epithelial cells, differed significantly among multiple BV test, but not between the A- and A+ groups.ConclusionsMetagenomics analysis can greatly expand our current understanding of vaginal microbial diversity in health and disease. Metagenomics profiling may also provide more reliable diagnostic criteria for BV testing.